电子学报 ›› 2018, Vol. 46 ›› Issue (7): 1545-1552.DOI: 10.3969/j.issn.0372-2112.2018.07.002

• 学术论文 • 上一篇    下一篇

基于最小二乘代价函数的卷积码盲识别方法

于沛东, 彭华, 巩克现, 陈泽亮   

  1. 解放军信息工程大学, 河南郑州 450002
  • 收稿日期:2016-11-09 修回日期:2017-05-17 出版日期:2018-07-25 发布日期:2018-07-25
  • 作者简介:于沛东,男,1988年12月出生,湖南慈利人,解放军信息工程大学博士生,主要研究方向为信道编码参数分析.E-mail:yupeidong1234@foxmail.com;彭华,男,1973年8月出生,江西萍乡人,解放军信息工程大学教授、博士生导师,主要研究方向为软件无线电、通信信号处理等.
  • 基金资助:
    国家自然科学基金(No.61401511)

Blind Recognition of Convolutional Codes Based on Least-Square Cost-Function

YU Pei-dong, PENG Hua, GONG Ke-xian, CHEN Ze-liang   

  1. PLA Information Engineering University, Zhengzhou, Henan 450002, China
  • Received:2016-11-09 Revised:2017-05-17 Online:2018-07-25 Published:2018-07-25

摘要: 卷积码的盲识别是级联码、Turbo码等高性能编码盲识别的基础,这要求卷积码盲识别方法具有较高的抗噪能力.使用接收解调的软判决信息是提高抗噪能力的关键.本文首先通过理论分析,从概率分布的角度解释现有软判决方法抗噪能力不足的原因,即汉明重量较小的候选解向量会严重削弱现有方法的识别正确概率.然后,提出一种基于最小二乘代价函数的解决方案,理论证明它能够有效减轻汉明重量对识别性能的影响.最后,通过仿真实验,对理论分析的结论进行验证.理论和实验表明,所提的新方法能将卷积码盲识别的抗噪能力提升约1dB.

关键词: 编码盲识别, 卷积码, Walsh-Hadamard变换, 对数似然比(LLR), 最小二乘

Abstract: Blind recognition of convolutional codes is the basis for recognition of certain high performance codes including concatenated and Turbo Code.It requires that the recognition methods for convolutional codes should have strong robustness against channel noise.The key to such purpose is to make use of the received soft information.Firstly,this paper gives a probabilistic analysis about the reason why the existing methods using soft information performs no better than the method based on hard information.The reason is that the candidate solution vectors of low Hamming weights seriously deteriorate the correct recognition probability.Then,a solution based on least-square cost function is proposed for this problem.Theoretical analysis proves that the impact of low Hamming weights can be effectively reduced.Finally,the theoretical results are verified by simulation experiments.Both the theory and the simulations show that,for blind recognition of convolutional codes,the proposed method improves the robustness against noise by about 1dB.

Key words: blind recognition of codes, convolutional code, Walsh-Hadamard Transform, log-likelihood ratio (LLR), least square

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